Independent employee
Owns a dedicated service account and role: granted system permissions like a real employee, executing tasks under its own identity with full execution records.
Capabilities
Every core capability of the AI-native CRM and agent governance layer: identity and authority, the growth loop, governance and audit, deployment topologies, CLI and developer workflows, IM integrations, and mobile.
Digital Workforce
Every digital employee has an explicit authorization subject — identity determines where permissions come from.
Owns a dedicated service account and role: granted system permissions like a real employee, executing tasks under its own identity with full execution records.
Acts within the initiating user’s permissions for each task — authority is inherited, scoped, and traceable.
ReAct-style stepwise execution with tool calls, human approval checkpoints, handoffs, and result write-backs; unauthenticated calls are denied by default.
Growth Loop
Digital employees get more valuable over time — because every correction is captured. Improvements pass a release gate; humans stay in the loop.
Human corrections, tool failures, knowledge gaps, and SOP drift are recognized and structured into reviewable improvement recommendations (prompts, SOPs, guardrails, model routing, eval suites).
Nothing reaches production behavior without tests, simulation, human approval, and regression against baseline — there is no path that bypasses the gate.
Prompt versions, SOPs, guardrail rules, model routing, and eval suites are exportable, versioned, rollback-able digital assets — not disposable config files.
Human CRM operations are distilled into SOPs and injected into knowledge retrieval — your team’s best practice becomes how digital employees work.
Governance
From permissions to traces, retrieval to budgets — every step is auditable.
Agent executions, reasoning steps, tool calls, approval decisions, and outbox events are fully recorded — replayable and attributable.
Knowledge retrieval (RAG) checks workspace, role, and object-read permissions per candidate — deny by default; out-of-scope content never enters context.
Guardrails bound behavior; model usage is metered per workspace with visible cost and configurable ceilings.
Deployment
One kernel, three topologies — choose by data boundary and compute.
Ready on activation; database, cache, and object storage are managed by the platform.
The system runs in the cloud while model inference runs on your own AI PC / intranet machine: models and sensitive data stay inside your network.
Single-node private delivery, or self-host the open-source Community edition (AGPL-3.0-only) with Docker Compose — full stack measured ready in 35s (2026-08-15, single-host Docker).
Developers
The full digital-employee lifecycle, from your terminal.
npm install --global @nexusclawhq/cli: org login, workspace and metadata management, deployment and release flows — credentials encrypted locally.
nexus workforce * covers learning loops, cognition, config writes, evals, ops, orchestration, and observation — run your digital workforce without the UI.
The same CLI works across your laptop, CI, and servers with consistent auth and fail-closed target resolution.
Integrations
Digital employees live where your team already works.
Headless integrations with full signature, encryption, and gateway contract alignment — digital employees take tasks and return results inside your existing IM.
A mobile work surface for approvals, review, and light operations.
A metadata-driven object/field/permission system — define custom business objects under the same governance chain.
Scope note: the above reflects currently delivered capabilities. The growth loop is a human-gated governance loop (human corrections and real outcomes consolidated through a release gate) and is not an autonomous self-evolution promise. The open-source Community edition (AGPL-3.0-only) ships the governance-kernel subset — see the GitHub repository.